Data-Driven Product Development Transformation: A Case Study from the Perspective of Adaptive Change in Organizational Routines

Extant research mostly focuses on the impact of big data on product development (PD) process and performance, and yet there is a lack of theoretical exploration of the transformation path, realization mechanism and transformation paradigm while moving from experience -based PD (EBPD) to data -driven PD (DDPD). This paper, from the integrated perspective of adaptive change and organizational routines, and based on an in-depth case study of HSTYLE, proposes a two -stage transformation model for moving from EBPD to DDPD, dissects the adaptive change mechanism of organizational routines for DDPD, puts forward a theoretical model for the transformation paradigm for DDPD, and provides an innovative interpretation of the connotation of data -driven. This paper constructs a theory for DDPD transformation that comprises three aspects: transformation path, realization mechanism and transformation paradigm. Conclusions of this paper have policy implications for enterprises in their practice on data -driven product innovation in the digital economy era.